{"id":"W2184515612","doi":"","title":"Fuzzy Liability Driven Pension Fund Management","year":2014,"lang":"en","type":"article","venue":"","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pension; Pension fund; Fuzzy logic; Actuarial science; Valuation (finance); Pension plan; Business; Target date fund; Finance; Liability; Economics; Computer science; Institutional investor; Artificial intelligence; Open-end fund","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001941756,0.00008068353,0.0001363238,0.0001277143,0.0001138616,0.0001474131,0.0002611397,0.00004310064,0.0008814483],"category_scores_gemma":[0.0002864088,0.00005232925,0.00006487621,0.0004006655,0.00003981336,0.0002111158,0.0001308725,0.00004401282,0.00188155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001355589,"about_ca_system_score_gemma":0.000006703907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002088502,"about_ca_topic_score_gemma":0.00003041004,"domain_scores_codex":[0.998215,0.0001473732,0.0003563577,0.000369899,0.0007597824,0.0001515779],"domain_scores_gemma":[0.9987312,0.0002630783,0.00009287924,0.0006723777,0.0001519871,0.00008848208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003867753,0.0001367657,0.1034948,0.000004366992,0.00001358209,0.000005931649,0.0002506752,0.01813293,0.0000646673,0.1840171,0.1334553,0.5603853],"study_design_scores_gemma":[0.0003535465,0.00006931402,0.1689953,0.000004310977,0.00001237046,0.00000269843,0.0002225596,0.04212863,0.0001392512,0.1483881,0.6394972,0.0001867577],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1204095,0.000007651312,0.08058704,0.000805289,0.0004094208,0.0001753122,7.953674e-7,0.00006709105,0.7975379],"genre_scores_gemma":[0.9550855,0.00006058583,0.01410998,0.0003543739,0.00005946379,0.000004183296,0.00000359112,0.000004896791,0.03031739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8346761,"threshold_uncertainty_score":0.9988956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09013101779956224,"score_gpt":0.3690352988641497,"score_spread":0.2789042810645874,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}